The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also be inventions.
Time series data is a sequence of data points, typically consisting of successive measurements made over a time interval. Examples of time series data are ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. Time series data is frequently plotted via line charts. Many domains of applied science and engineering that involve temporal measurements use time series data. Time series data analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series data forecasting is the use of a model to predict future values based on previously observed values. A time series database is a computer system that is optimized for handling time series data. In some fields, time series data is called a profile, a curve, or a trace. Despite the disparate names, many of the same mathematical operations, queries, or database transactions are useful for analyzing each of these time series data types. The implementation of a computerized database system that can correctly, reliably, and efficiently implement these operations must be specialized for time series data.